[HIRING] Technical AI Automation Specialist — Long-Term Team Collaboration

Jobs
161

Hi Ahmed — the “build, test, deploy, monitor, maintain” part of your post is the part I care about most, so here is exactly where I sit against your list.
What I have in production:

  • n8n as the orchestration layer. DispatchAI (GitHub - MAhsaanUllah/DispatchAI · GitHub) runs seven authenticated webhook flows (create booking, check availability, find customer, reschedule, cancel, booking automation) behind a shared secret, with idempotency keys and conflict checks so a repeated request cannot double-book, bounded retries, error branches and a notification outbox. Workflow exports are version-controlled and the README documents what each flow connects to. 71 tests run in CI.
  • Voice agents end to end. The same DispatchAI system is driven by an ElevenLabs voice agent alongside a React dashboard, so I have built the caller side of a system like your example: intent captured, details collected, booking written through the API, confirmation sent.
  • LLM APIs and webhooks: OpenAI, Claude, Gemini and local models through Ollama; webhook signature verification; structured output validated with Pydantic and Zod before anything executes.
  • Databases and deployment: PostgreSQL with row-level isolation, SQLite, Redis, Docker, Linux and VPS deployment, GitHub Actions CI, plus monitoring through structured logs, retries and an outbox so a failed step is visible instead of silent.
  • Lead handling and messaging: a live WhatsApp agent (tarkabot.online) that qualifies incoming messages in Roman Urdu and English, structures them into orders or bookings, and hands off to a human when intent is unclear. 32 tests.
    Straight about the gaps: I have not used Retell, Vapi or Twilio yet — my voice work is ElevenLabs, and my telephony-adjacent work is WhatsApp through an Evolution API bridge. The auth, webhook, booking and handoff patterns carry over, and I would rather name that up front than pretend.
    How I work: sandbox first with test credentials and synthetic data, workflow exported as version-controlled JSON, documentation covering what it does, what it connects to and how to maintain it, then maintenance after launch. I keep scope written down and flag risks early rather than at the deadline.
    Available 20+ hours per week, PKT (UTC+5), and I am looking for exactly this: one team, ongoing client work, not one-off tasks. Happy to start with a small paid piece so you can judge the quality before anything longer.
162

Hi Ahmed,

1. Short introduction:
I’m Hadi, a full-stack AI automation developer specializing in AI voice agents and n8n automation. I build complete production systems, voice/chat agents, lead qualification, CRM and calendar integrations, exactly the kind of end-to-end systems you described, for international clients. I’m looking for exactly this: a long-term technical collaboration with a growing agency.

2. Strongest technical skills:
n8n automation, AI voice agents (Retell, VAPI, ElevenLabs, OpenAI Realtime), REST APIs and webhooks, CRM and calendar integrations, Twilio telephony, OpenAI/Claude LLM APIs, and production thinking, error handling, retries, human handoff, logging, and monitoring. Comfortable with JavaScript/Python for custom logic.

3. Experience with n8n:
n8n is my core tool. I build and maintain complex production workflows, multi-step automations, API/webhook orchestration, lead pipelines, and AI-agent logic, self-hosted. I’m comfortable debugging messy workflows, handling API failures gracefully, and building systems that stay reliable in production.

4. Experience with Retell / VAPI / Twilio:
I build real-time AI voice agents with VAPI, Retell, and OpenAI Realtime, including inbound/outbound calling, intent understanding, lead qualification, and appointment booking, with Twilio for telephony and number provisioning. I have a live AI voice agent on my site you can actually talk to.

5. 2-3 AI automation projects I personally built:

  • A real-time AI voice agent (OpenAI Realtime, secure ephemeral-token architecture) that holds natural conversations, live and interactive on my portfolio.
  • An end-to-end lead engine: AI enrichment, personalized outreach, timed follow-ups, and AI-powered outbound calling (n8n, Twilio, ElevenLabs), with error handling so no lead is dropped.
  • A custom CRM with an AI assistant that drafts in the user’s own voice using a knowledge base (React, Supabase, PGVector, n8n).

6. Links / demos:
Portfolio with live AI voice and chat agents you can interact with: https://hadiai.dev

7. What I personally handled in those projects:
Everything, architecture, the n8n workflows, the voice agent design and prompts, API/webhook integrations, the database layer, error handling, deployment, and documentation. I build these solo end to end, so I own the full stack of each system.

8. Expected compensation / rate:
Flexible depending on the working model, roughly $20-30/hour for ongoing project work, or we can agree per-project rates. Happy to discuss what fits the agency stage.

9. Preferred working model:
Ongoing, project-based collaboration as client work comes in, exactly the long-term relationship you described. Open to a retainer or per-project structure.

10. Availability:
Available immediately and can commit consistent hours.

11. Timezone:
Pakistan (GMT+5). I regularly overlap with US, UK, and European hours for international clients, so scheduling overlap won’t be an issue.

12. Time to build a production-ready AI receptionist like your example:
For the flow you described (incoming call → AI voice agent → intent → collect details → qualify → book appointment → update CRM → notify → human transfer for urgent), roughly 1-2 weeks for a solid, tested production version, depending on the CRM/calendar specifics and telephony setup. The core can be working within days; the rest is testing, edge cases, error handling, and monitoring to make it genuinely production-ready.

Looking forward to hearing more, this is exactly the kind of long-term technical role I want to be part of.

Best,
Hadi

163

Hi, I am Ankit. My background spans workflow automation, recruitment operations, financial research and Python, and I’m currently working hands-on with n8n + AI/LLM automation.

1. introduction
I enjoy building end to end automations that connect AI with real business processes rather than isolated AI demos. My recent work has focused on research/intelligence, recruitment and outreach automation.

2. Strongest technical skills
n8n, AI/LLM workflows, REST APIs, webhooks, Google Sheets, structured data processing, JavaScript/Python, prompt design, scoring/routing logic, validation, debugging and workflow automation.

3. n8n experience
I have built multi-step n8n workflows involving multiple data sources, API based research/enrichment, LLM processing, structured JSON outputs, scoring, routing, deduplication, validation, reporting and downstream automation.

4. Retell / Vapi / Twilio
I have not yet deployed a production voice agent system using Retell, Vapi or Twilio, so I don’t want to overstate my experience here. My hands on strength is currently n8n, LLM orchestration, APIs/webhooks and business process automation, and I am comfortable learning and integrating additional API-driven platforms.

5. AI automation projects I personally built

AI Influencer Outreach & Lead Intelligence System: an n8n workflow for influencer discovery and qualification. It processes creator information such as audience size, views and location, identifies available contact/business routes, scores prospects, selects the best contact route and prepares qualified leads for outreach.

AI Recruitment Automation: candidate/JD intake → normalization → AI-assisted candidate evaluation → skills-gap analysis → match scoring → output validation → recruiter reporting.
Demo: https://drive.google.com/file/d/1iro4SVKq_6GJTwkM2RC8uYn_r4l6C_Wn/view?usp=sharing

AI Financial Market Intelligence System: multi-source information collection, deduplication, research/API enrichment, LLM analysis and scoring, structured outputs and downstream content/reporting automation.
GitHub: GitHub - annkiit88/n8n-financial-market-intelligence: AI-powered financial market intelligence automation built with n8n, AI agents, web research and APIs for news analysis, scoring and structured insights. · GitHub

6 What I personally handled
I personally worked on the workflow architecture, n8n implementation, API/data flows, LLM prompting, structured outputs, scoring/routing logic, validation and debugging. I have also worked through real issues involving API failures, rate limits, malformed LLM outputs, deduplication problems and failed workflow executions.

7. Expected compensation
I am flexible at this stage and open to fixed-price projects/milestones based on scope and complexity. For a longer-term arrangement, I’d be happy to discuss a structure that works for both sides.

8. Preferred working model
Remote and project-based initially, with a strong preference for long-term collaboration if we work well together.

9. Availability
I can start immediately.

10. Timezone
IST (UTC+5:30), with flexibility for scheduled overlap with other time zones.

11. AI receptionist timeline
For a clearly scoped first production-ready version similar to your example, I would roughly estimate 1–2 weeks, including integrations, testing and basic failure handling. Before committing to an exact timeline, I’d want to understand the chosen voice platform, CRM, calendar, telephony setup, qualification logic, human-handoff requirements and expected edge cases.

What particularly interests me about your opportunity is the focus on Build → Test → Deploy → Monitor → Maintain. I’m looking for exactly this kind of work where automation needs to function reliably as part of a real business process, and I’d be interested in growing with the agency long term.

164
  1. Alexey — AI automation engineer, founder/sales background, remote from Cyprus.
  2. n8n, LLM agents with tool calling, RAG, Python/FastAPI, PostgreSQL, API/webhook integrations, CRM sync.
  3. n8n self-hosted in production since 2024 — assistant, lead-qualification and data workflows, with error branches, retries and alerts.
  4. Retell/Vapi/Twilio: call transcription and call-recording pipelines into a knowledge base in production; dialogue scripts and objection handling are my home turf from 10+ years in sales. Retell/Vapi agents I’d set up on your first project.
    5–7. Personally built, end to end:
    — AI lead-qualification bot: 3 questions → structured lead to the owner in real time, 6 tracked events. I did the dialogue design, backend and analytics.
    — Multi-agent research pipeline: ~$0.05 per 30-page sourced report. Architecture, code, deploy — all mine.
    — n8n assistant with LLM steps (finance, tasks, screenshot parsing). Mine.
    Demos: https://nichr.tech
  5. $40–60/h or fixed per build.
  6. Contract, white-label is fine.
  7. 20–30 h/week, can start this week.
  8. UTC+3.
  9. A production-ready receptionist like your example (booking, FAQ, CRM write, human handoff, call logging): about 1–2 weeks for the first one, days for the next ones on the same template.

— Alexey · https://nichr.tech · support@nichr.tech

165

I have 4+ years building n8n workflows and integrating AI tools like OpenAI and Claude into automation pipelines.

Can you share more about the specific AI use cases you need automated? That will help me explain how I’ve handled similar setups.

My rate is $25/hour and I’m available for long term collaboration.

167

Hi Ahmed,

Intro: I’m Nil, 21, an AI automation builder based in Spain (UTC+2). I’ve worked with n8n, Make, Zapier and APIs for about 3 years.

Skills: n8n, Make, REST APIs, webhooks, Google Apps Script, and AI agents with tool use over live data.

Projects (all built solo, end to end):

  • An AI agent connected to a CRM database: natural-language queries with tool use. Demo: https://youtu.be/_AbRAQ5sQWc
  • A hotel chatbot with reservation capture and email notifications (Node.js + OpenAI)
  • A quoting tool with PDF generation, used daily by a real business

Retell/Vapi/Twilio: I haven’t used them in production yet. API orchestration is the core of my work, and I’d pick up the voice layer quickly.

Availability: Remote, around 20 hours/week.

Compensation: $27/h, or a fixed price per task. Happy to start with a small paid task.

AI receptionist estimate: I’d rather scope it properly after a short call, since it depends on the voice stack and integrations you use.

Thanks for your time.

168

Hi, I’m an automation engineer with ~2 years’ experience, 200+ n8n workflows delivered, and hands-on AI-assisted development (using Claude to generate/debug custom JS/Python integration logic). Interested in long-term collaboration — happy to share examples of what I’ve built and discuss fit.

169

Hi Ahmed,

1. Intro: I’m Hatem, a Cairo-based full-stack and AI automation engineer with about 5 years of client work. I’m an AI Trainer at micro1, where I train frontier models on reasoning and frontend code. I also co-founded Tawabiry, a queue and booking platform for clinics and salons, so I know appointment flows from the business owner’s side too.

2. Strongest skills: TypeScript/JavaScript (Node, Next.js), Python, REST APIs and webhooks, n8n, LLM APIs (OpenAI, Gemini, Claude), local LLMs (Ollama), Redis, Postgres/Supabase, Git, and deployment on Render and Vercel.

3. n8n: I’ve shipped n8n workflows that run in production and completed tixu.ai’s Advanced AI Agents (n8n) program. When n8n isn’t enough, I drop into Python or Node for the heavier logic.

4. Retell / Vapi / Twilio: I haven’t used these in production yet. I built a voice-AI front-desk demo directly on Google Gemini’s real-time voice, so I know the voice-agent flow: intent, data capture, handoff. Retell and Vapi wrap the same pieces, and I’d be productive on them quickly.

5–7. Projects I personally built:

  • Crypto signal aggregator (client): a TradingView Pine Script sends webhooks to a Python service on Render, Redis groups the signals, and everything goes out through Telegram. It covers about 150 tickers across every timeframe in one alert channel. I built, deployed and debugged the whole pipeline.
  • Pulse EGX (live, commercial): daily Sharia-screened BUY/HOLD/SELL signals for 72 Egyptian Exchange stocks, delivered on Telegram to 5 members. The EGX has no public API, so I built the data pipeline around that. I own it end to end: data, screening logic, delivery and the site.
  • Ghost Outbound: B2B lead research running on local 70B models. It finds prospects, gathers their details in one place and ranks the best fits, which is lead qualification before any outreach. I designed and built it.

Links:
Portfolio: https://hatemsoliman.dev
GitHub: CodeNKoffee (Hatem Soliman) · GitHub
Pulse EGX: https://pulseegx.hatemsoliman.dev
Case studies (ERC relief data sync, crypto aggregator, industrial platform audit): Automations READMEs - Google Drive
RAVEN GP autonomous car: https://ravengp-ai.vercel.app/

8. Rate: $42/hour, or a fixed quote per build.

9. Working model: long-term contractor. I’d build each client’s system, then keep it running on a monthly maintenance retainer.

10. Availability: flexible per project. I scale up during builds and stay on call for monitoring between them.

11. Timezone: Cairo (GMT+3 until late October, then GMT+2).

12. AI receptionist timeline: about 2 weeks for the first production-ready version, including testing against real call scenarios. That covers retries and error workflows on every API call, validation of names, phone numbers and dates before anything touches the CRM, duplicate-booking protection, a human-transfer fallback, logging, and alerts when something fails. Once templated, the next clients take 3–5 days.

Best,
Hatem Soliman
hatemsoliman.dev
Your Digital Nomad :snow_capped_mountain::four_leaf_clover:

170

Hi Ahmed,

I’m interested in the long-term technical automation role.

My strongest hands-on areas are n8n, REST APIs, webhooks, LLM integrations, structured AI workflows, data processing, JavaScript and workflow reliability.

I’m particularly interested in the n8n/API/CRM/lead qualification side of your systems. I haven’t shipped a production Retell/Vapi/Twilio voice system yet, so I don’t want to overstate that experience, but I’m comfortable with API-based integrations and can learn the platform-specific layer quickly.

I’d suggest starting with a small paid n8n/API/CRM workflow or repair task. That gives you a direct way to evaluate how I build, test, document and handle failure cases before moving into larger client systems.

I’m available for ongoing project-based work and can start immediately.

Best,
Vahid